This invention relates to a geospatial information creating system, and more particularly, to a technology of extracting a house footprint from aerial photograph and satellite imagery.
Geospatial information of houses (specifically house footprint) is very important for cadastral management. It is normally highly expensive to acquire such information through either conventional ground survey or manual digitization of aerial photograph. Extraction of house footprints from remote sensing image data (which includes, in addition to aerial photograph, satellite imagery and both of them are hereafter collectively referred to as “aerial photograph”) is a very promising solution for updating geospatial information system (GIS) data. However, this task has remained a challenge in past decades due to its high complexity.
Though intensive efforts to extract house footprint have been conducted in past decades, there still is no automatic tool proposed for reliably extracting house footprint, as described in Gulch, E. and Muller, H. New applications of semi-automatic building acquisition. In Automatic Extraction of Man-Made Objects From Aerial and Space Images (III), Edited by Emmanuel P. Baltsavias, Armin Gruen, Luc Van Gool. ISBN: 90-5809-252-6. by A.A. BALKEMA PUBLISHERS, pp. 103-114. 2001. The conventional methods generally fall into two categories according to their primitive features used. One is based on edge-linking to link edges of houses along house boundaries. Another one is based on region growth algorithm to generate house regions by merging similar neighboring pixels.
However, both methods are very much sensitive to noise and incapable of dealing with complex cases such as weak edges and occlusion, therefore these methods are only applicable to very few practical cases. Currently, although semi-automatic systems are most efficient, they can hardly generate a house footprint map with correct geometric shape.
Mayunga, S. D., Zhang, Y. and Coleman, D. J. Semi-automatic building extraction utilizing Quickbird imagery. In Stilla, U. Rottensteiner, F. and Hinz, S. (Eds) CMRT05. IAPRS, Vol. XXXVI, Part 3/W24—Vienna, Austria, Aug. 29-30, 2005 describes a method based on dynamic contour model (for example, snake model), which deforms contour through minimizing an energy function, and generates an initial contour using “radial casting” algorithm. This method allows semi-automatic extraction of buildings from satellite imagery (for example, image taken by Quickbird). However, house footprints extracted according to “radial casting” algorithm are coarse and irregular, and hence the method can not solve the problem.
US 2004/0263514 A1 describes a semi-automatic method to extract house boundaries by linking the edges near the initial points given by user, but the method described in US 2004/0263514 A1 is insufficient to determine whether the edges really belong to target houses.
JP 2003-346144 A describes a method to use air-borne laser scanning data for segmenting house regions and then combining image data to extract house footprints. However, the method described in JP 2003-346144 A will very much increase the data cost by using laser scanning and also introduces uncertainty by combing data from different sources.